Our fast-growing team is seeking a Data Engineer to support our teams by ensuring high quality of the data used for the machine learning training and evaluation tasks. Your responsibilities will include the following:
- Data acquisition: get new data from various sources; translate ML-training needs into specific data requirements.
- Preparation for machine learning: select data for annotation; formulate annotation goals and requirements; convert annotated data to ML-ready datasets.
- Ensuring data quality and quality of the training: develop ML / statistical models for cleaning the data and ensuring its versatility; develop, test and implement relevant metrics; develop data formats for various training strategies; develop models for comparing datasets.
- Prepare data for evaluation needs.
- Scaling and automation of the above.
Preferred Qualifications and Experience:
- Computer science, mathematics, or other relevant engineering/science background.
- Good knowledge of statistics.
- Knowledge of at least one scripting programming language; ability to quickly write efficient shell scripts for everyday data-related tasks.
- Experience working with data or in data-heavy field.
- Ability to reason about data in quantitative terms.
Experience in aerospace engineering or avionics is not required; we will teach you everything you need to know about the constraints of safety critical systems in airworthy applications.
- Combine the best of both worlds: a) work in fast-growing startup and b) collaborate with and learn from very experienced engineers and scientists that have previously worked at Google, SpaceX, CERN, Imperial College, and ETH Zürich.
- Build cutting-edge technology that will shape our future.
- Join our pilots to test your ideas in the air during test flights in the Swiss Alps.
- Develop scarce and marketable skills in machine learning, computer vision and robotics that are relevant beyond aviation (e.g., autonomous driving, medical applications, pharmaceuticals)
How to Apply:
Send your Resume/CV, including your portfolio of projects to firstname.lastname@example.org
. Tell us a bit about yourself, why you think you are a good fit for us and why we are a good fit for you.